The artificial intelligence dividend: Firm-level profitability and the asymmetric impact of gulf cooperation council technology policies - Alharithi, Mohammed (Asian Economic and Financial Review, 2025)
We examine the asymmetric effects of national Artificial Intelligence (AI) and diversification policies on firm-level profitability in the Gulf Cooperation Council (GCC), addressing a critical gap in the microeconomic literature on the region's technology-driven transition. Using a dynamic panel dataset of 53 strategically essential firms across all six GCC countries from 2015 to 2024, we employ a Difference-in-Differences (DiD) approach, complemented by System Generalized Method of Moments (SGMM) estimation, to establish causal relationships while rigorously addressing concerns about endogeneity. The results reveal that AI-focused policies boosted profitability in firms actively investing in AI, with policy milestones increasing asset-based returns by 2.1% and equity-based returns by 2.8%. In comparison, government subsidies dedicated to the AI sector amplified these effects by an additional 4.5% and 6.5%, respectively. The positive impact of these policies grew even stronger after 2020. For firms deeply invested in AI, targeted subsidies led to profitability increases of 8.8% on assets and 13.1% on equity. In stark contrast, companies in traditional, non-AI sectors showed no statistically meaningful improvement from the same policy measures. These findings highlight the power of well-targeted fiscal incentives and selective policy support for the AI sector in promoting successful economic diversification. They offer a valuable blueprint for policymakers in resource-rich nations aiming to build sustainable, knowledge-based economies by making strategic technological investments. Notable limitations include the study's focus on large, strategic firms and its timeframe, which captures only the initial phase of AI policy implementation.